Computer Vision Engineer

About the Role

Key Responsibilities

• Develop and optimize computer vision pipelines for real-time and scalable performance in production environments.
• Design, develop, and implement computer vision algorithms for applications such as image classification, object detection, and segmentation.
• Train and fine-tune deep learning models (e.g., CNNs, RNNs) for visual data analysis, ensuring high accuracy and performance.
• Perform data preprocessing, augmentation, and develop annotation tools for large-scale image and video datasets.
• Collaborate with cross-functional teams, including software engineers and hardware engineers, to integrate vision systems into products.
• Conduct experiments and evaluations to measure the performance and efficiency of vision algorithms.
• Implement and test solutions on various hardware platforms (e.g., GPUs, embedded systems, edge devices).
• Stay up to date with the latest research, trends, and advancements in computer vision and machine learning.
• Troubleshoot and resolve issues related to model accuracy, performance, and system integration.
• Provide technical documentation and support for computer vision solutions and algorithms.
• Ensure the deployment of robust and maintainable vision-based systems in real-world applications.
• Optimize algorithms for computational efficiency, including memory and processing time constraints.
• Maintain integrity of customer, company standards, and requirements during development activities.

Requirements

• Strong foundation in computer vision techniques, machine learning, and programming.
• Proficiency in computer vision algorithms and feature extraction methods (e.g., SIFT, HOG).
• Mastery of deep learning models and classical machine learning principles.
• Experience with linear and logistic regression, SVMs, decision trees (Random Forests and boosting), k-Nearest Neighbors, and probabilistic classifiers.
• Competence in programming languages such as Python and C++.

Nice to Have

• Bachelor's degree in Computer Science, Electrical Engineering, Robotics, Mathematics, or a related field.
• Experience in deploying real-world applications.
• Knowledge of CNNs and RNNs for visual data analysis.
• Familiarity with YOLO and unmanned systems.

Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, Robotics, Mathematics, or a related field.

Benefits & Perks

• Medical, Dental & Vision Insurance Coverage
• Life/ADD & Short/Long Term Disability Insurance
• 401(k) Savings Plan
• Employee Stock Purchase Plan (ESPP)
• Paid Time-Off (PTO)
• Holidays
• Education Reimbursement